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After 10 years of science communication since graduating from Tsinghua, how do I push back against AI?

Liu Aiqi (online name "laq is a hamster"), a graduate of Tsinghua's School of Life Sciences, has been doing science communication for 10 years, with over one million followers across platforms, and his audio program "Science in Plain Words" has accumulated over 5 million plays. He mentioned that in 2025 a University of Zurich team deployed 34 AI bots on Reddit, with persuasion efficiency 3 to 6 times that of humans; another experiment involving 1,682 adults showed that stories written by AI scored higher than those by humans, but scores rose when they were labeled "written by a human." His way of resisting is: give literary quality back to readers, give expression back to oneself, and give people back to face-to-face interaction.

Building Real-Time Speech Applications on SageMaker AI with vLLM-Omni (Part 1)

AWS has published a tutorial demonstrating how to deploy Qwen3-TTS on Amazon SageMaker AI using the vLLM-Omni Deep Learning Container, enabling text streaming in and 24 kHz PCM audio chunks streaming out through SageMaker bidirectional streaming connections, along with a companion Gradio application. This DLC is based on vLLM-Omni v1.5 and adds the bidirectional streaming capability labels and routing middleware required by SageMaker AI; the example uses the native WebSocket route v1/audio/speech/stream.

Generating Images and Videos with vLLM-Omni on SageMaker AI (Part 2)

On Amazon SageMaker AI, deploy two endpoints using the same AWS vLLM-Omni DLC image: a real-time endpoint running FLUX.2-klein-4B to generate images, and an asynchronous endpoint running Wan2.1-VACE-1.3B for image-conditioned video generation. A text prompt first generates a PNG, which is then sent along with a motion prompt to the video endpoint; the generated MP4 is retrieved from Amazon S3, and the example also provides a command-line workflow and an optional Streamlit interface.

Modal Labs is nearing completion of a $750 million funding round at a valuation of $15.75 billion

According to people familiar with the matter, AI inference infrastructure provider Modal Labs is nearing completion of a $750 million funding round led by Accel at a valuation of $15.75 billion, more than tripling its $465 million valuation from four months ago. Modal Labs declined to comment. The round comes amid surging demand for inference services, with inference startups such as Baseten, Fireworks, and Fal also in talks to raise at higher valuations. Modal was founded in 2021 and is headquartered in New York, with about 150 employees. Its customers include Cognition, Suno, Ramp, and Substack, and its annualized revenue had exceeded $300 million as of May. In July of this year, Modal disclosed that a customer's data was leaked in a malicious OpenAI agent attack campaign targeting Hugging Face; its CTO said the issue stemmed from a vulnerability in the customer's own code and that the platform was not breached.

GPT-6 Family's First Model Astra Released, Author's Hands-On Test Consumed 4 Billion Tokens

OpenAI released Astra, which the author calls the beginning of the GPT-6 family; it performs outstandingly on ARC-AGI-3 and scored highest on Zapier's AutomationBench, with pricing the same as Fable 5.1. During weekend trials, the author consumed 4 billion tokens and found its capability fluctuates noticeably—it is a showcase model rather than one that reliably does work. Astra in Codex can now continue advancing tasks without waiting for an answer, and OpenAI also claims it has achieved its automated research intern goal, with the next goal being an automated AI researcher by March 2028.

Ethan Mollick Tries GPT-5.5 Early: Capability Gains Are Still Accelerating

Ethan Mollick was granted early access to try GPT-5.5 and believes its capabilities have improved markedly; GPT-5.5 Pro completed the same 3D port town simulation task in 20 minutes, compared with 33 minutes for the previous generation, GPT-5.4 Pro. Using Codex together with GPT-5.5 to process a decade's backlog of his own crowdfunding data, he generated a paper including a genuine literature review and statistical methods with just four prompts, and he considers its quality equivalent to a second-year PhD project. He also noted that OpenAI's new image model (sometimes called GPT-imagegen-2) can render high-quality text and images, but that AI still has rough edges in long-form fiction writing, such as florid prose and homogeneous dialogue.

Ethan Mollick: An opinionated guide to using AI right now

Ethan Mollick has published an opinionated guide to using AI right now, suggesting that people use OpenAI's published real-world usage data to judge when to use free models and when to upgrade to paid. He points out that the four most advanced systems are Claude, Gemini, ChatGPT, and Grok, with paid tiers at $20 per month or about $200 per month; the former suits most people, while the latter is aimed at complex technical and programming needs. For serious work, he recommends manually selecting an Agent model, such as GPT-5 Thinking Extended or GPT-5 Thinking Heavy.

A Review of Research on Gender Bias in AI

AI models reflect and even amplify real-world gender bias, and quantifying these biases is a prerequisite for mitigating the problem. The article reviews research on gender-stereotyped analogies in word embeddings, facial recognition systems' error rate of up to 34.7% for darker-skinned women (versus only 0.8% for lighter-skinned men), and coreference resolution models' tendency to associate occupations with male pronouns.